Google launches Cloud AutoML, a self-training AI that helps you build your very own custom AI system
Have you ever thought of building your own custom AI system? Google might be able to help you. For the first time, Google revelead one of the internal artificial intelligence tools that it used to build other artificially intelligent systems. The new service dubbed, Cloud AutoML, uses multiple machine-learning tricks to automatically build and train a deep-learning algorithm that can recognize things in images. With this tool, Google now makes it a lot easier for anyone to build its very own custom AI system. Users can now train high quality custom machine learning models with minimum effort and machine learning expertise. The technology is currently in Alpha stage and anyone can request access via Google Cloud Platform page.
According to Google, Cloud AutoML is a suite of Machine Learning products that enables developers with limited machine learning expertise to train high quality models by leveraging Google’s state of the art transfer learning, and Neural Architecture Search technology. Cloud AutoML provides a simple graphical user interface (GUI) for you to train, evaluate, improve, and deploy models based on your own data. You’re only a few minutes away from your own custom machine learning model. It comes with a lot of features. At its core, AutoML is fully integrated with other Google Cloud services. It provide customers with a consistent method of access across the entire Google Cloud service line. You can also store the training data in Google Cloud Storage. To generate a prediction on your trained model, developers and users can simply use the existing Vision API by adding a parameter for your custom model, or use Cloud ML Engine’s online prediction service. AutoML also leverages Leverages Google state of the art AutoML and Transfer Learning technology to produce high quality models.
A couple of organizations are already putting AutoML to test and getting great results. Among them are, Disney, Urban Outfitters and ZSL. “Urban Outfitters is constantly looking for new ways to enhance our customers’ shopping experience. Creating and maintaining a comprehensive set of product attributes is critical to providing our customers relevant product recommendations, accurate search results, and helpful product filters; however, manually creating product attributes is arduous and time-consuming. To address this, our team has been evaluating Cloud AutoML to automate the product attribution process by recognizing nuanced product characteristics like patterns and neck lines styles. Cloud AutoML has great promise to help our customers with better discovery, recommendation, and search experiences,” Alan Rosenwinkel Ph.D., Data Scientist at Urban Outfitters said.
“We need to scale AI out to more people,” Fei-Fei Li, chief scientist at Google Cloud, said ahead of the launch today. Li estimates there are at most a few thousand people worldwide with the expertise needed to build the very best deep-learning models. “But there are an estimated 21 million developers worldwide today,” she says. “We want to reach out to them all, and make AI accessible to these developers.” “You don’t need a Ph.D. in machine learning,” said Diane Greene, who oversees Google’s cloud computing group. “But you can still build a highly accurate machine learning model.”